Global Trends in Technology, Media & Telecommunications

What issues are top-of-mind for executives in Technology, Media & Entertainment, and Telecommunications (TMT)? Our essay series offers succinct insights from global TMT leaders about opportunities for success across the rapidly changing TMT ecosystem.

Consumers: getting smarter about smartphones?

For nearly two decades, Deloitte Global has issued an annual Predictions report, which focuses on trends, transformation and opportunity across the telecommunications, technology, media and entertainment ecosystem. This year, one of our 11 Predictions incorporated data from Deloitte’s recent Global Mobile Consumer Survey to consider how consumer smartphone behavior may evolve in 2018 and beyond.

When looking at how consumers may interact with their mobile devices going forward, Deloitte Global predicts that most adults of all ages will continue to be comfortable using their phones a lot—even hundreds of times per day. Instead of “always, anytime, for anything” usage, however, we predict that consumers will become more focused about their smartphone interactions, and will consider changing their behavior usage when it is distracting them from activities that they want (or need) to concentrate on more fully. Already, we’ve seen an effort to avoid distracted driving; consumers in 2018 may also take steps to limit distracted sleeping, distracted walking and distracted talking.

Deloitte Global predicts that 45 percent of global adult smartphone users in 2018 will worry they are using their phones too much for certain activities, and will consider actions that refine usage, including deleting certain apps, turning off audio notifications, and keeping devices stored in a briefcase or purse. Further, Deloitte Global predicts this concern will be highest for young people who have smartphones, with nearly two-thirds of 18- to 24-year-olds around the world feeling they are using their devices too much, and with over half trying to control usage.

Deloitte Global notes the need to exercise caution in defining appropriate smartphone usage. Smartphones now act as figurative Swiss Army Knives for consumer needs, serving as wristwatches, radios, TVs, computers, cameras, video recorders, maps, newspapers, gaming devices, magazines and much more. Placed in that context, glancing at a phone 50 or more times per day is not, in and of itself, a sign of excessive use; rather, it shows what an exceedingly useful device the smartphone is. In addition, potential distractions during activities such as driving may be reduced as smartphone technologies continue to become more sophisticated—for example, voice recognition, personal digital assistants, Bluetooth devices and other hands-free functionality.

Moreover, there is variation in attitudes and behaviors around the world. Fewer than one in five Japanese smartphone owners think they use their smartphone excessively, while nearly three in four Mexicans with smartphones are concerned and nearly two-thirds were actively trying to limit usage. In most countries, the percentages of those worried about overuse and of those trying to cut back were very similar. In the Nordic countries, the proportion of Finns worried about phone usage was about half that of Norwegians.

And of course, not all usage is equal. Checking one’s phone while watching TV or a film, commuting on public transit, or out shopping is generally benign. According to the Predictions report, it seems likely that when people talk about cutting back on phone usage, they are not talking about these instances.

Bottom line

Both for the telecom industry and for individual users, the goal should not be to strive for some arbitrary number of glances at a phone each day. In fact, as consumers watch ever more video on smartphones instead of TVs, as they perform work tasks on smartphones instead of computers and as m-commerce continues moving to the smartphone, Deloitte Global believes that the number of daily glances will continue to rise.

Instead, the focus for 2018 can be on balance in usage. It is possible that with new technologies to promote safety, along with increasing consumer awareness of good phone etiquette, that consumer behavior patterns may organically change. This in turn presents new opportunities for phone manufacturers, software/app developers and network operators to explore growth in areas like increased m-commerce, m-payments and maturing smartphone apps. The powerful combination of consumer behavior and enterprise opportunity is likely to help us to stay safe, engaged—and get the most from our valued mobile devices.

2018: A watershed year for machine learning?

Deloitte Global recently released its annual Predictions report, which looks at transformation and opportunity in tech, media and telecom over the next one to five years. In part of our report, Deloitte Global predicts that in 2018, large and medium-sized enterprises will intensify their use of machine learning (ML)—an artificial intelligence, or cognitive, technology that enables systems to learn and improve from exposure to data without being programmed explicitly. Deloitte Global predicts that the number of implementations and pilot projects using the technology will double compared with 2017, and they will have doubled again by 2020.

Today, most enterprises using ML have only a handful of deployments and pilots under way, but, according to Deloitte Global, progress in five key areas should make it easier and faster to develop ML solutions. These vectors of progress are:

Automating data science. Time-consuming ML tasks, such as data exploration and feature engineering, are increasingly likely to be automated. A growing number of tools and techniques for data science automation, offered by established companies as well as venture-backed start-ups, should help shrink the time required to execute an ML proof of concept.

Reducing the need for training data. Training an ML model can require up to millions of data elements. A number of promising techniques are emerging that aim to reduce the amount of training data required for ML—for example, a team at Deloitte Consulting LLP tested a tool that was able to build an accurate model with only a fifth of the training data previously required. Another technique that could reduce the need for training data is transfer learning, in which an ML model is pre-trained on one data set as a shortcut to learning a new data set in a similar domain.

Accelerating training. Hardware manufacturers are developing specialized hardware to slash the time required to train ML models by accelerating the calculations required and the transfer of data within the chip. These dedicated processors can help companies speed up ML training and execution manyfold, which in turn brings down the associated costs. Early adopters of these specialized AI chips include major technology vendors and research institutions in data science and ML, but adoption is spreading to sectors such as retail, financial services and telecom.

Explaining results. ML achievements get more impressive by the day, but many are “black boxes,” meaning it is not possible to explain with confidence how they make their decisions. This presents challenges, for reasons ranging from trust in the answers generated by a model—as when customers are offered incentives—to regulatory compliance.

A number of techniques have been created that help shine light into the black box of certain ML models, making them more interpretable and accurate. As it becomes possible to build interpretable ML models, companies in highly regulated industries such as financial services, life sciences and health care can be expected to intensify their use of ML via pilots and deployments over coming years.

Deploying locally. ML use will grow along with the ability to deploy it where it is needed. ML is increasingly coming to mobile devices and smart sensors, expanding the technology’s applications to smart homes and cities, autonomous vehicles, wearable technology, and industrial IoT.

In response, technology vendors are creating compact ML software models to undertake tasks such as image recognition and language translation on portable devices. Semiconductor vendors are developing their own power-efficient AI chips to bring ML to mobile devices. With smartphones an increasingly viable deployment option for ML, the number of potential applications is growing.

The bottom line

Collectively, the five vectors of ML progress should double the intensity with which enterprises are using this technology by the end of 2018. In the long term, these vectors should help make ML a mainstream technology. Enterprises interested in ML may wish to consider the following:

Look for opportunities to automate some of the work of oversubscribed data scientists, and ask consultants how they can use data science automation.

Monitor emerging techniques, such as data synthesis and transfer learning, that could ease the bottleneck often created by the challenge of acquiring training data.

Find out what computing resources optimized for ML are offered by their cloud providers. If they are running workloads in their own data centers, they may want to investigate adding specialized hardware to the mix.

Explore state-of-the-art techniques for improving interpretability that may not yet be in the commercial mainstream.

Track the performance benchmarks being reported by makers of next-generation chips, to help predict when on-device deployment is likely to become feasible.

Interested in learning more? Our full Predictions report is available at www.deloitte.com/predictions, and a recent US cognitive technology survey is online at www.deloitte.com/us/cognitivesurvey. As always, I welcome your thoughts and feedback.Today, most enterprises using ML have only a handful of deployments and pilots under way, but, according to Deloitte Global, progress in five key areas should make it easier and faster to develop ML solutions. These vectors of progress are:

Sign up now! Global growth in digital subscriptions

Recently, Deloitte Global released its 2018 Predictions report, which considers what trends may transform and disrupt media, entertainment, technology and telecommunications in 2018 and beyond. This year’s report contains 11 separate Predictions, many relevant to companies in the media and entertainment ecosystem.

In one Prediction, Deloitte Global asserts that by the end of 2018, 50 percent of adults in developed countries will have at least two online-only media subscriptions, and by the end of 2020, that average will have doubled to four. In total, Deloitte Global estimates there will be 680 million subscriptions and about 350 million subscribers this year.

The report further predicts that a fifth of adults in developed countries will pay for or have access to at least five paid-for online media subscriptions, and by the end of 2020, they will have 10. For these adults, aggregate spend on digital subscriptions they have access to (paid for by themselves or by someone in the household) is likely to average over $100 per month by 2020, or over $1,200 annually.

Here’s a quick overview of how different categories of digital subscriptions may grow.

Online TV and movie services

At the start of 2018, we expect there will be about 375 million subscription video-on-demand (SVOD) subscriptions worldwide. The number of SVOD services a household may have access to is likely to increase through the end of the decade as more production houses and content owners launch over-the-top (OTT) services. By the end of 2020, we expect that in mature SVOD markets such as the US, an individual may subscribe or have access to multiple TV services spanning many genres, including drama, comedy, sports and kids.

In non-English-speaking markets, we expect more local language content to be created to drive demand for OTT services. As more local language content is developed, SVOD services will broaden their appeal; fluency in English or a willingness to consume dubbed or subtitled content will no longer be necessary.

Online news

By the end of 2018, we expect there will be about 20 million digital-only news subscriptions worldwide. We expect news providers to focus increasingly on generating revenue from subscriptions, typically as a complement to advertising, given the challenges they have encountered during years of reliance on ad revenue alone. Whereas certain titles had a 10:90 ratio of subscription to ad revenue in 2012, we predict it may be 50:50 by 2020.

Music

By the end of 2018, we expect there will be about 150+ million music subscriptions. Subscriptions for music services are about $10 per month in the US, €10 in Europe and £10 in the UK – about the price of a CD. In 2015, the average per-stream rate for online music videos worldwide was $0.001, half as much as in the previous year. $10 is equivalent, in revenue terms, to the royalties for 1,000 streams.

Growth should continue to increase for years to come – the number of subscribers is still a fraction of the number of ad-funded consumers, and any smartphone can be a repository of or a conduit to music services.

Video games

At the start of 2018, we expect there will be about 35 million subscribers to video game networks that enable online play. The number of subscribers may appear quite small, but it is worth bearing in mind that the number of latest-generation consoles is likely to remain under 100 million at the end of 2018, so 35 percent penetration is quite respectable. Furthermore, at $5 per month, 35 million subscribers are worth an additional $2.1 billion in annual and predictable revenue on top of the money made by selling the games and consoles in the first place.

Growth in the number of online subscriptions is likely to be driven by an increased emphasis on online multiplayer, rather than individual, games.

Bottom line

The total number of online media subscriptions, as well as the average number of subscriptions per individual and household, should grow by at least 20 percent in 2018 and continue to increase in the medium term. This is a positive development for the media industry.

It is also the case that the media industry cannot rely on online subscriptions alone; the sector should also remain focused on advertising – but with ad formats and an ad load appropriate to its customer base.

Finally, the media industry should also consider how best to sell content on an individual article, track or edition basis, and other revenue models, including tips and contributions, should also be considered.

What’s your take on the future of digital subscriptions? I welcome your comments and invite you to read the full 2018 Predictions report.

Valleys of the World: A virtual fund-of-funds approach to frontier investing

I’ve been thinking lately about the accelerating corporate trend of setting up venture funds—and the seeming inevitability of Silicon Valley as the destination for these funds. Sure, some of the world’s greatest innovation stories have emerged from the corridor between San Jose and San Francisco. Sure, the Valley is inundated with unicorns. Sure, there are thousands of promising start-ups there that need financial backing today. All those things may be true, but still I wonder whether there are other ways to invest, innovate, and grow in the venture world—or if doing so really does require making an “all in” Silicon Valley play.

Looking beyond Silicon Valley

Silicon Valley has, beyond a doubt, produced some of the world’s game-changing businesses, and therefore merits considerable investment attention. But asset prices in the Valley are buoyed by steady and significant capital flows, not to mention free marketing in the form of extensive media coverage, and the cost of setting up shop to invest in Valley start-ups makes doing so not for the faint of heart.

That’s why I was excited when I visited Tel Aviv for the first time, in early 2016, and came away with a strong sense of two things:

1. Israel has a fine array of start-ups, with groundbreaking IP—and top talent behind it. In effect, Israel has established its own “valley”—and is justifiably proud of it. But here, asset prices and the costs of investing are noticeably less than in Silicon Valley.

2. There are probably other “valleys” around the world, which do not get the same degree of investment attention as Silicon Valley but also feature great assets, intellectual property, and capital—making them attractive investment opportunities.

That’s my hypothesis: There are many “valleys” in the world. Wherever there are innovation centres fuelled by government incentives and digitally connected talent—places like Tel Aviv, Berlin, Moscow, Bangalore, and even Shenzhen and Beijing—there are attractive investment propositions.

Creating a globally diversified frontier investment fund

So, how does a company get exposed to a fully diversified and globally rich choice of assets that meet their investment parameters—without getting bogged down in excessive and fixed set-up and infrastructure costs?

The challenge is to manage a range of factors that can inhibit an ideal global investment architecture, ensuring that the investing company can secure the best assets available, at the best prices available and an acceptable cost of investing, on a global scale.

Imagine a virtual “fund of funds” (VFOF) approach to frontier investing, where a portfolio of investment funds is created. It’s virtual because we don’t want to get slowed down by all the administrative and legal bureaucracy involved in setting up actual funds. Here’s how it works for our VFOF of the world’s “valleys”:

Each individual fund is dedicated to one of the “valleys” we’ve chosen to invest in, and has an allocation designed to give the overall fund of funds risk diversification and reduced investment volatility as well as a truly global investment landscape.

The fund percentage is strategically determined based on a combination of factors: strategic ambitions, risk appetite, investment parameters, investment time horizons, asset price trends, the costs of funding, etc.

This approach will likely appeal to a corporate board whose questions around “What investment opportunities are we still missing here?” and “How do we mitigate against exogenous risk factors related to a specific market?” are easily answered. Many board members worry about diversification as an important compass guide in any event, as it’s the safest way to guide a business through the complexity of today’s business world.

Each fund can then have its own performance metrics, and asset comparisons and monitoring can be done in a relevant fund context.

The real magic, of course, will be in the implementation. Many company executives will say, “We’d love this but just don’t have the infrastructure to do this—it’s why we invest the way we do” or “We have little choice and can’t just wait around, so co-investing with trusted players in established markets, well, what’s wrong with that?”

We’ve been working on some ideas and I believe there is an answer—that creating global investment leverage without significant consequential costs is a real possibility. An illustrative model of what’s involved is presented below.

The magic of the process occurs in the interplay between the theory of digitivity, the Red Queen hypothesis, and a range of future industry scenarios – it’s important to have as much optionality as possible built in.

Three keys to success for adopting a flexible-consumption business model

Today, the world’s internet users number in the billions. Technology-enabled newcomers are disrupting industries, from healthcare and transportation to retail and media. And companies of all kinds are pushing the technological envelope to the point that self-driving cars and drone-based product-delivery systems are becoming viable.

It might seem that the digital era, which took flight in earnest a quarter-century ago with the popularization of the World Wide Web, is already mature. But it’s actually just beginning, especially for the enterprise. The changes of the past few decades—in how we communicate, shop, work, consume media, and more—are minor in comparison with what’s to come.

Evolving business models

For companies across all industries, one major trend will be the continuing transition away from producing and selling physical products, to service-based solutions supporting flexible consumption models. Instead of purchasing on-premise servers, for instance, enterprises are increasingly likely to turn to infrastructure-as-a-service (IaaS) solutions. And instead of buying shrink-wrapped software, businesses are more and more likely to subscribe to software-as-a-service (SaaS) solutions.

Powered by machine learning, advanced analytics, falling prices for bandwidth, and processing power and ubiquitous connectivity, this transition promises to keep accelerating. As companies of all kinds, producing everything from printers to jet engine manufacturers, increasingly adopt flexible-consumption, service-delivery models, buyers will benefit from lower upfront costs (along with a shift in spending from CAPEX to OPEX), instant scalability, increased agility, and lower risk.

Service-delivery models offer benefits, including more predictable revenue streams and enhanced customer engagement. Instead of touching the customer only at the point of sale (and possibly later, if issues arise with the product), organizations that offer goods and services via a flexible consumption model have the opportunity to build and maintain an ongoing relationship—which can lead to greater brand loyalty, decreased selling costs, and new ways to create value for customers that drive increased revenue.

Transforming your company for success

To make a successful transition from selling products to providing services, companies need to consider three critical concepts:

Be ready to embrace a fundamentally new business model. This transition will affect every aspect of the business, including Branding, Investor Relations, R&D and product development, IT infrastructure and operations, sales-force training and compensation, tax, and regulatory compliance.

Don’t underestimate the effort required. The challenges of making a transition to a flexible consumption model are many and varied. The regulatory and tax implications of shifting from selling products to providing subscription services can be complex, especially if you operate internationally and/or operate multiple businesses. Each and every business unit and function of the enterprise will have its own transformational roadmap with unique issues and opportunities to assess.

Make a plan for transforming your business. The complexities of orchestrating a top-to-bottom transformation are significant and no business discipline or function can be left behind. A successful transition to a services-focused model requires getting all stakeholders aligned and executing in concert—from your management team to your partners and vendors. Achieving success requires a clear model of the transformation journey; a detailed roadmap defining opportunities, milestones, and metrics; and good governance involving all stakeholders.

Whether you’re ready for it or not, the shift to flexible-consumption models is happening, and it’s accelerating rapidly. Whether you adapt successfully is up to you.

Three Steps to More Successful Media M&A Deals

As Warren Buffet says, “Price is what you pay. Value is what you get.” Among M&A dealmakers, too often the focus is on the price aspect of the deal—CEOs haggling over and agreeing to terms. But what happens after the handshake—how the companies are integrated—is given short shrift. The result? Deals that fail to deliver the expected value.

This is particularly true of deals involving media companies, which can be vastly different from companies in other sectors, and difficult to integrate as a result.

Smart media M&A dealmakers see the handshake as just the beginning of any given deal. Before that fateful moment, they look forward to assess whether and how their companies can be integrated in three important areas: culture, operations, and cash flow and forecasting.

For instance, telecommunications and technology companies are currently buying up media companies for impressive sums, hoping to create value by bringing together content creation and distribution. (See Comcast’s acquisition of NBC Universal, Verizon’s acquisitions of AOL and Yahoo, and AT&T’s acquisition of Time-Warner.) Telcos and tech companies, which are often engineering focused, usually have very different cultures from media companies, which, relatively, tend to employ lots of creative types and have cultures that reflect that fact.

Integrating corporate cultures is an art form—but it’s essential if you want your deal to generate value. Give this factor the attention it requires to get it right.

Operations

Companies involved in mergers and acquisitions typically hope to drive operational efficiencies in areas from supply chain, manufacturing, and marketing to distribution and customer service. But because media company operations are typically so distinct from those in other industries, integrating operations after a media M&A deal can be especially challenging. And because the media business can involve taking sizeable financial risks—content creation and acquisition costs can be enormous, but there’s no guarantee that the marketplace will be interested in your content—answering the question of how your combined company will integrate operations is of the utmost importance to driving deal value.

It’s also important to consider issues related to the legal structures involved in, and the tax implications of, the deal. Often, for example, media companies and other businesses take very different approaches to asset structuring. If you’re not careful, media M&A deals can have suboptimal tax consequences, and generate lots of extra work for both management and boards.

Cash flow and forecasting

Companies in media M&A deals can have significantly different cash-flow profiles. Media companies with subscription-based business models generate predictable cash flows, compared to industries where cash flows and forecasts are lumpier—like tech. As dividend plays, meanwhile, telcos desire steady cash flow—but media M&A targets don’t necessarily map to the telco cash-flow profile. Moreover, there may be significant cash opportunities at the outset of an M&A deal, which could affect the new entity’s taxation. How will you combine the companies in your media merger or acquisition? Have a clear answer if you want the deal to work.

Listen to Mr. Buffet, no slouch at M&A himself. For a successful media M&A deal, look beyond the terms of the deal to how, exactly, your companies are going to integrate. You—and your investors—will be glad you did.

What’s your take on media M&A? Have anything to add? Join the conversation below.

Listen to Mr. Buffet, no slouch at M&A himself. For a successful media M&A deal, look beyond the terms of the deal to how, exactly, your companies are going to integrate. You—and your investors—will be glad you did.

What’s your take on media M&A? Have anything to add? Join the conversation on LinkedIn or Twitter.

Get in touch

Director | Financial Advisory

Janis serves as the AML, Sanctions and Financial Crime Leader at Deloitte Central Europe, and leads the Financial Services Industry (FSI) Advisory and Forensic services in the Baltic States. He has 1... More

Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee (“DTTL”), its network of member firms, and their related entities. DTTL and each of its member firms are legally separate and independent entities. DTTL (also referred to as “Deloitte Global”) does not provide services to clients. Please see About Deloitte for a detailed description of DTTL and its member firms.